Multiple Choice Question

Overfitting is a common problem when a model learns too much from the training data.

What does "overfitting" refer to in machine learning?

A

A model performing well on both training and test data
B

A model performing poorly on training data but well on test data
C

A model performing well on training data but poorly on test data
D

A model that generalizes well to unseen data
E

A model that performs equally on all datasets

Explanation:

Overfitting occurs when a model is too complex and captures noise in the training data, leading to poor generalization on new data.

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